An application of fuzzy collaborative intelligence to unit cost forecasting with partial data access by security consideration

Advances in Mechanical Engineering

2013

Self Cite

Productivity is always considered as one of the most basic and important factors to the competitiveness of a factory. For this reason, all factories have sought to enhance productivity. To achieve this goal, we first need to estimate the productivity. However, there is considerable degree of uncertainty in productivity. For this reason, a fuzzy collaborative forecasting approach is proposed in this study to forecast the productivity of a factory. First, a learning model is established to estimate the future productivity. Subsequently, the learning model is converted into three equivalent nonlinear programming problems to be solved from various viewpoints. The fuzzy productivity forecasts by different experts may not be equal and should therefore be aggregated. To this end, the fuzzy intersection and back propagation network approach is applied. The practical example of a dynamic random access memory (DRAM) factory is used to evaluate the effectiveness of the proposed methodology.

Section: Methodsmentioning

confidence: 99%

“…Chen [26] applied the same method to predict the foreign exchange rate. Chen [27] considered Table 2: The differences between the proposed methodology and the previous fuzzy collaborative forecasting methods.…”

Section: Related Workmentioning

confidence: 99%

A Fuzzy Collaborative Forecasting Approach for Forecasting the Productivity of a Factory

Wang

Advances in Mechanical Engineering

2013

Self Cite

“…The fuzzy forecasts obtained by different experts are aggregated using a fuzzy intersection, resulting in a polygon-shaped fuzzy number, which can be defuzzified using a back propagation network. Chen [4] considered the case in which each expert has only partial access to the data, and is not willing to share the raw data he/she owns. The forecasting results by an expert are conveyed to other experts for the modification of their settings, so that the actual values will be contained in the fuzzy forecasts after collaboration.…”

Section: Related Workmentioning

confidence: 99%

Forecasting the Unit Cost of a Product with Some Linear Fuzzy Collaborative Forecasting Models

2012

Algorithms

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Forecasting the unit cost of every product type in a factory is an important task. However, it is not easy to deal with the uncertainty of the unit cost. Fuzzy collaborative forecasting is a very effective treatment of the uncertainty in the distributed environment. This paper presents some linear fuzzy collaborative forecasting models to predict the unit cost of a product. In these models, the experts’ forecasts differ and therefore need to be aggregated through collaboration. According to the experimental results, the effectiveness of forecasting the unit cost was considerably improved through collaboration

“…The corners of the polygon-shaped fuzzy number are then fed into a BPN to generate the final forecast which is a crisp value. Chen (2011a) proposed a fuzzy collaborative forecasting approach, in which each expert has only partial access to the unit cost data, and is not willing to share the raw data he/she owns. The forecasting results by an expert are conveyed to other experts to modify their settings, so that the actual values will be contained in the fuzzy forecasts after collaboration.…”

Section: Introductionmentioning

confidence: 99%

“…In Chen and Lin (2008) and Chen (2009b), fuzzy collaborative forecasting methods based on the yield learning model were proposed to predict the yield of a semiconductor product. Another fuzzy collaborative forecasting method was applied to estimate the unit cost per die in Chen (2011aChen ( , 2011b. In estimating the work-in-progress (WIP) level, the fuzzy collaborative forecasting method also achieved a very good performance (Chen et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Some Linear Fuzzy Collaborative Forecasting Models for Semiconductor Unit Cost Forecasting

International Journal of Fuzzy System Applications

2013

Self Cite

Forecasting the unit cost of every product type in a factory is an important task to the factory. However, it is not easy to deal with the uncertainty in the unit cost. Fuzzy collaborative forecasting is very effective in handling the uncertainty in the distributed environment. This paper presents some fuzzy collaborative forecasting models to predict the unit cost of a semiconductor product. According to the experimental results, the effectiveness of forecasting the unit cost was considerably improved through the objects’ collaboration.